DatalabUpdateInput

pydantic model openapi_client.models.datalab_update_input.DatalabUpdateInput

Fields to change on an existing datalab. Only these fields are accepted; the name and type cannot be changed. Ignored entirely when starting or stopping the datalab.

Fields:

• additional_metadata (openapi_client.models.datalab_update_input_additional_metadata.DatalabUpdateInputAdditionalMetadata | None)

• compute_metadata (openapi_client.models.datalab_update_input_compute_metadata.DatalabUpdateInputComputeMetadata | None)

• description (str | None)

• resource_access_metadata (openapi_client.models.datalab_update_input_resource_access_metadata.DatalabUpdateInputResourceAccessMetadata | None)

field description: Optional[StrictStr] = None (alias 'Description')

field compute_metadata: Optional[DatalabUpdateInputComputeMetadata] = None (alias 'ComputeMetadata')

field resource_access_metadata: Optional[DatalabUpdateInputResourceAccessMetadata] = None (alias 'ResourceAccessMetadata')

field additional_metadata: Optional[DatalabUpdateInputAdditionalMetadata] = None (alias 'AdditionalMetadata')

to_str()

Returns the string representation of the model using alias

Return type:

str

to_json()

Returns the JSON representation of the model using alias

Return type:

str

classmethod from_json(json_str)

Create an instance of DatalabUpdateInput from a JSON string

Return type:

Optional[Self]

to_dict()

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic’s self.model_dump(by_alias=True):

• None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.

Return type:

Dict[str, Any]

classmethod from_dict(obj)

Create an instance of DatalabUpdateInput from a dict

Return type:

Optional[Self]